International Research Journal of Engineering and Technology (IRJET) e-ISSN: 2395 -0056 Volume: 03 Issue: 06 | June-2016 www.irjet.net p-ISSN: 2395-0072 © 2016, IRJET ISO 9001:2008 Certified Journal Page 2198 Opinion Mining of Customer Reviews based on their Score using Machine Learning Techniques Miss. Lovenika Kushwaha 1 , Mr. Sunil Damodar Rathod 2 1 PG Student, Computer Engineering Department, Dr. D.Y.Patil SOE Lohegaon, SPP University Pune, India 2 Asst. Prof., Computer Engineering Department, Dr. D.Y.Patil SOE Lohegaon, SPP University Pune, India ---------------------------------------------------------------------***--------------------------------------------------------------------- Abstract - Websites for online shopping is becoming more and more popular nowadays. Companies are eager to know about their customer buying behavior to increase their product sale. Extracting knowledge from large database, Data Mining is the key approach to use for accurate result. But in our context, we have to process customer reviews from large E-commerce, database for which Opinion Mining is the best approach for mining customer reviews about the product. The widely available internet resources are letting the users to shop any products anywhere, anytime at any cost. With the brisk development in the 3G and 4G we can expect a tremendous development in the area of M-commerce and E-commerce. In existing papers, opinion mining is used to process the online product reviews, feature and recommend the best product among others. Natural Language Processing (NLP) and Naive Bayes classification both are used to determine the polarity of reviews (obtain a polarity score from negative review and positive review). In this paper a novel technique is proposed for opinion mining and feature extraction of product reviews. The objective is to encourage the customers and assist them in choosing the right product. It is based on natural language processing, opinion mining and AdaBoost classifier. Results indicate that the proposed methods are highly effective and efficient in performing their tasks. We will also aim at improving the accuracy of our opinion polarity detection and feature extraction among other techniques. Key Words: Opinion Mining, Part-of-speech (POS) Tagging, Natural Language Processing (NLP), Sentiment Analysis, Naïve Bayes Classification and AdaBoost classifier. 1. INTRODUCTION As we all know very well that E-Commerce sites are gaining popularity across all over the world. Customers are migrating towards online purchases more instead of going to the markets because of its easiness, convenience, reliability, and rapidness. There are a number of Online shopping websites that are available on the internet, such as Amazon, Flipkart, Snapdeal, Jabong, Myntra, Paytm, Zovi, etc. These websites allow the users to buy products with ease and lesser prize. A lot of attractive and day-to-day useful products like books, electronic goods, home appliances, clothing, and footwear are sold from these sites. These websites provide an option to the customers to write their review about their product that they buy from these sites. These reviews or opinions are very helpful to the users, manufacturers of the product as well as the developers of the website. The users who are in quandary to buy a product can read the reviews about the particular product from these websites so that they can have a view about their product before buying it and also know which is on the 1 st position. Potential buyers can make decisions based on the reviews of customers who have purchased and experienced the product. The manufacturers of the product will be able to know the minor or major drawbacks of the product from the reviews which helps the manufacturers to get a chance to release the updated version of the product which satisfies the reviews that are mentioned in the websites. Hence online reviews play a significant role in understanding the